AI AGENTS

Fact-check guest and inbound blog submissions on intake

When a draft arrives by email, an agent verifies its factual claims against sources and replies to the author with a pass/revise verdict plus the exact claims that need a citation.

CategoryAI Agents
Enginepaperclip
Difficultybeginner
Triggerevent
Steps5
Setup~5 min

How it runs

The automated pipeline, trigger to output.

  • TriggerNew draft email to submissions inboxGmailGmail
  • ActionExtract draft text and itemize claimsOpenAI
  • ActionSearch for supporting primary sourcesBraveBrave Search
  • LogicAll claims sourced, or gaps found?
  • OutputReply to author with verdict and required citationsGmailGmail

What it does

Guest posts and agency drafts arrive full of confident assertions and zero footnotes. This agent intercepts each inbound draft by email, extracts its claims, searches for supporting primary sources, and emails the author back a structured verdict: which claims are sourced, which need a citation, and which appear false — turning a vague "we'll review it" into a concrete revision list.

When to use it

For editorial teams accepting external contributions who want a consistent first-pass factual screen before a human editor spends time on a piece.

How it works

  1. 1A new email to the submissions inbox triggers the run.
  2. 2The agent extracts the draft text from the message body or attachment.
  3. 3OpenAI itemizes the factual claims in the draft.
  4. 4It searches Brave Search for supporting sources and reads the strongest results.
  5. 5A branch decides pass (all claims sourced) versus revise (gaps or contradictions).
  6. 6A reply email goes to the author with the verdict and the specific claims requiring citations.

Set it up

What you configure once, before turning it on.

  1. 1
    Connect GmailRead, draft, send, label.
  2. 2
    Connect OpenAIModels, embeddings, files.
  3. 3
    Connect Brave SearchWeb, news, image, video search.
  4. 4
    Set each agent's modelWe leave models unset so you pick the tier — fast + cheap, or top-quality.
  5. 5
    Tune it to your dataEdit the prompts, filters, and field mappings so it matches how your team works.
  6. 6
    Test, then turn it onRun once against a sample, confirm the output, then enable the trigger.

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